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Evaluating Prior Knowledge of ARC Using World Models

KSC, 2023

Extracting the core knowledge of ARC with the World Model

KSC, 2023

Regulation Using Large Language Models to Generate Synthetic Data for Evaluating Analogical Ability

Donghyeon Shin*, Seungpil Lee*, Klea Lena Kovacec, and Sundong Kim†

In IJCAI Workshop on Analogical Abstraction in Cognition, Perception, and Language, 2024, 2024

ARCLE: The Abstract and Reasoning Corpus Learning Environment for Reinforcement Learning

Hosung Lee*, Sejin Kim*, Seungpil Lee, Sanha Hwang, Jihwan Lee, Byung-Jun Lee†, and Sundong Kim†

In CoLLAs, 2024, 2024

From Generation to Selection: Findings of Converting Analogical Problem-Solving into Multiple-Choice Questions

Donghyeon Shin*, Seungpil Lee*, Klea Lena Kovacec, and Sundong Kim†

In EMNLP Findings, 2024, 2024

Reasoning Abilities of Large Language Models through the Lens of Abstraction and Reasoning (Extended Abstract of the below paper)

Seungpil Lee*, Woochang Sim*, Donghyeon Shin*, Sejin Kim and Sundong Kim†

In NeurIPS Workshop on System-2 Reasoning at Scale, 2024, 2025

Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus

Seungpil Lee*, Woochang Sim*, Donghyeon Shin*, Wongyu Seo, Jiwon Park, Seokki Lee, Sanha Hwang, Sejin Kim and Sundong Kim†

ACM Transactions on Intelligent Systems and Technology (Accept with Minor Revision), 2024, 2025

Solution Augmentation for ARC-AGI Problems Using GFlowNet: A Probabilistic Exploration Approach

Sanha Hwang, Seungpil Lee, Sejin Kim, and Sundong Kim†

Transactions on Machine Learning Research, 2025

Can Large Language Models Develop Gambling Addiction?

Seungpil Lee*, Donghyeon Shin, Yunjeong Lee and Sundong Kim†

arXiv preprint, 2025

PAPER
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publications

Evaluating Prior Knowledge of ARC Using World Models

KSC, 2023

Extracting the core knowledge of ARC with the World Model

KSC, 2023

ARCLE: The Abstract and Reasoning Corpus Learning Environment for Reinforcement Learning

Hosung Lee*, Sejin Kim*, Seungpil Lee, Sanha Hwang, Jihwan Lee, Byung-Jun Lee†, and Sundong Kim†

In CoLLAs, 2024, 2024

Regulation Using Large Language Models to Generate Synthetic Data for Evaluating Analogical Ability

Donghyeon Shin*, Seungpil Lee*, Klea Lena Kovacec, and Sundong Kim†

In IJCAI Workshop on Analogical Abstraction in Cognition, Perception, and Language, 2024, 2024

From Generation to Selection: Findings of Converting Analogical Problem-Solving into Multiple-Choice Questions

Donghyeon Shin*, Seungpil Lee*, Klea Lena Kovacec, and Sundong Kim†

In EMNLP Findings, 2024, 2024

Reasoning Abilities of Large Language Models through the Lens of Abstraction and Reasoning (Extended Abstract of the below paper)

Seungpil Lee*, Woochang Sim*, Donghyeon Shin*, Sejin Kim and Sundong Kim†

In NeurIPS Workshop on System-2 Reasoning at Scale, 2024, 2025

Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus

Seungpil Lee*, Woochang Sim*, Donghyeon Shin*, Wongyu Seo, Jiwon Park, Seokki Lee, Sanha Hwang, Sejin Kim and Sundong Kim†

ACM Transactions on Intelligent Systems and Technology (Accept with Minor Revision), 2024, 2025

Solution Augmentation for ARC-AGI Problems Using GFlowNet: A Probabilistic Exploration Approach

Sanha Hwang, Seungpil Lee, Sejin Kim, and Sundong Kim†

Transactions on Machine Learning Research, 2025

Can Large Language Models Develop Gambling Addiction?

Seungpil Lee*, Donghyeon Shin, Yunjeong Lee and Sundong Kim†

arXiv preprint, 2025

PAPER